{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "df7793e2-51ed-4c33-ac32-d332c5db1a9c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "最佳旋转角度: 58.16 度\n",
      "优化后无人机总移动距离: 617.76 单位\n",
      "局部优化后无人机总移动距离: 617.76 单位\n",
      "\n",
      "无人机初始位置数组 (x, y):\n",
      "无人机 1: (164.64, 214.56)\n",
      "无人机 2: (180.83, 163.46)\n",
      "无人机 3: (127.10, 193.77)\n",
      "无人机 4: (131.28, 267.53)\n",
      "无人机 5: (289.10, 115.03)\n",
      "无人机 6: (237.52, 158.67)\n",
      "无人机 7: (170.41, 277.68)\n",
      "无人机 8: (21.31, 26.14)\n",
      "无人机 9: (6.07, 249.79)\n",
      "无人机 10: (233.45, 261.00)\n",
      "无人机 11: (293.59, 239.75)\n",
      "无人机 12: (138.44, 234.16)\n",
      "无人机 13: (35.48, 191.98)\n",
      "无人机 14: (43.01, 283.40)\n",
      "无人机 15: (156.55, 124.40)\n",
      "\n",
      "目标位置数组 (x, y)（优化后）:\n",
      "无人机 1: (178.43, 179.38)\n",
      "无人机 2: (204.81, 136.91)\n",
      "无人机 3: (115.27, 199.02)\n",
      "无人机 4: (125.68, 264.34)\n",
      "无人机 5: (267.97, 117.27)\n",
      "无人机 6: (241.59, 159.75)\n",
      "无人机 7: (162.46, 287.18)\n",
      "无人机 8: (78.48, 176.18)\n",
      "无人机 9: (52.11, 218.65)\n",
      "无人机 10: (188.84, 244.70)\n",
      "无人机 11: (215.22, 202.23)\n",
      "无人机 12: (152.05, 221.86)\n",
      "无人机 13: (15.32, 195.81)\n",
      "无人机 14: (88.89, 241.50)\n",
      "无人机 15: (141.64, 156.54)\n",
      "\n",
      "各个无人机的移动距离:\n",
      "无人机 1: 移动距离 = 37.78 单位\n",
      "无人机 2: 移动距离 = 35.78 单位\n",
      "无人机 3: 移动距离 = 12.94 单位\n",
      "无人机 4: 移动距离 = 6.45 单位\n",
      "无人机 5: 移动距离 = 21.25 单位\n",
      "无人机 6: 移动距离 = 4.22 单位\n",
      "无人机 7: 移动距离 = 12.39 单位\n",
      "无人机 8: 移动距离 = 160.56 单位\n",
      "无人机 9: 移动距离 = 55.58 单位\n",
      "无人机 10: 移动距离 = 47.49 单位\n",
      "无人机 11: 移动距离 = 86.89 单位\n",
      "无人机 12: 移动距离 = 18.34 单位\n",
      "无人机 13: 移动距离 = 20.52 单位\n",
      "无人机 14: 移动距离 = 62.14 单位\n",
      "无人机 15: 移动距离 = 35.43 单位\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from scipy.optimize import linear_sum_assignment\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.spatial.transform import Rotation as R\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 使用黑体\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 解决负号显示问题\n",
    "\n",
    "# 随机生成15个初始无人机位置\n",
    "np.random.seed(0)  # 固定种子以便结果可重复\n",
    "initial_positions = np.random.rand(15, 2) * 300  # 假设范围在0到300之间\n",
    "\n",
    "# 等边三角形边长\n",
    "a = 50  # 边长可以根据实际需求调整\n",
    "\n",
    "# 构建理想的等边三角形矩阵\n",
    "triangle_positions = []\n",
    "for i in range(6):  # 我们有15个点，需要大约6行\n",
    "    for j in range(i + 1):\n",
    "        x = j * a\n",
    "        y = np.sqrt(3) / 2 * a * i\n",
    "        triangle_positions.append((x, y))\n",
    "triangle_positions = np.array(triangle_positions[:15])\n",
    "\n",
    "# 方法1：平移等边三角形阵列，使其质心与无人机初始位置的质心对齐\n",
    "initial_centroid = np.mean(initial_positions, axis=0)\n",
    "triangle_centroid = np.mean(triangle_positions, axis=0)\n",
    "translation_vector = initial_centroid - triangle_centroid\n",
    "translated_triangle_positions = triangle_positions + translation_vector\n",
    "\n",
    "# 方法2：旋转等边三角形阵列，以使其更贴近无人机的初始位置\n",
    "best_angle = 0\n",
    "min_total_distance = float('inf')\n",
    "for angle in np.linspace(0, 360, 360):  # 尝试0到360度的旋转\n",
    "    rotation_matrix = R.from_euler('z', angle, degrees=True).as_matrix()[:2, :2]\n",
    "    rotated_positions = np.dot(translated_triangle_positions - initial_centroid, rotation_matrix) + initial_centroid\n",
    "\n",
    "    distance_matrix = np.linalg.norm(initial_positions[:, np.newaxis] - rotated_positions[np.newaxis, :], axis=2)\n",
    "    row_ind, col_ind = linear_sum_assignment(distance_matrix)\n",
    "    total_distance = np.sum(distance_matrix[row_ind, col_ind])\n",
    "\n",
    "    if total_distance < min_total_distance:\n",
    "        min_total_distance = total_distance\n",
    "        best_angle = angle\n",
    "        best_positions = rotated_positions\n",
    "        best_row_ind = row_ind\n",
    "        best_col_ind = col_ind\n",
    "\n",
    "print(f\"\\n最佳旋转角度: {best_angle:.2f} 度\")\n",
    "print(f\"优化后无人机总移动距离: {min_total_distance:.2f} 单位\")\n",
    "\n",
    "# 局部搜索与交换策略进行进一步优化\n",
    "def local_search_swap(row_ind, col_ind, distance_matrix):\n",
    "    best_distance = np.sum(distance_matrix[row_ind, col_ind])\n",
    "    for i in range(len(row_ind)):\n",
    "        for j in range(i + 1, len(row_ind)):\n",
    "            new_col_ind = col_ind.copy()\n",
    "            # 交换两个匹配\n",
    "            new_col_ind[i], new_col_ind[j] = new_col_ind[j], new_col_ind[i]\n",
    "            new_distance = np.sum(distance_matrix[row_ind, new_col_ind])\n",
    "            if new_distance < best_distance:\n",
    "                best_distance = new_distance\n",
    "                col_ind = new_col_ind\n",
    "    return col_ind, best_distance\n",
    "\n",
    "# 通过局部搜索和交换优化结果\n",
    "final_col_ind, final_distance = local_search_swap(best_row_ind, best_col_ind, np.linalg.norm(initial_positions[:, np.newaxis] - best_positions[np.newaxis, :], axis=2))\n",
    "final_positions = best_positions[final_col_ind]\n",
    "\n",
    "print(f\"局部优化后无人机总移动距离: {final_distance:.2f} 单位\\n\")\n",
    "\n",
    "# 打印无人机的初始位置数组和目标位置数组\n",
    "print(\"无人机初始位置数组 (x, y):\")\n",
    "for i, pos in enumerate(initial_positions, 1):\n",
    "    print(f\"无人机 {i}: ({pos[0]:.2f}, {pos[1]:.2f})\")\n",
    "\n",
    "print(\"\\n目标位置数组 (x, y)（优化后）:\")\n",
    "for i, pos in enumerate(final_positions, 1):\n",
    "    print(f\"无人机 {i}: ({pos[0]:.2f}, {pos[1]:.2f})\")\n",
    "\n",
    "# 打印各个无人机的移动距离\n",
    "print(\"\\n各个无人机的移动距离:\")\n",
    "for i in range(len(initial_positions)):\n",
    "    distance = np.linalg.norm(initial_positions[i] - final_positions[i])\n",
    "    print(f\"无人机 {i+1}: 移动距离 = {distance:.2f} 单位\")\n",
    "\n",
    "# 可视化最终调整过程\n",
    "plt.figure(figsize=(12, 10))\n",
    "plt.scatter(initial_positions[:, 0], initial_positions[:, 1], c='blue', label='初始位置')\n",
    "plt.scatter(final_positions[:, 0], final_positions[:, 1], c='red', label='调整后位置')\n",
    "\n",
    "# 在图像中添加无人机编号\n",
    "for i in range(len(initial_positions)):\n",
    "    plt.text(initial_positions[i, 0], initial_positions[i, 1], str(i+1), fontsize=12, color='blue', ha='right')\n",
    "    plt.text(final_positions[i, 0], final_positions[i, 1], str(i+1), fontsize=12, color='red', ha='left')\n",
    "\n",
    "# 绘制调整路径\n",
    "for i in range(len(initial_positions)):\n",
    "    plt.plot([initial_positions[i, 0], final_positions[i, 0]],\n",
    "              [initial_positions[i, 1], final_positions[i, 1]], 'k--')\n",
    "\n",
    "# 设置图形参数（中文）\n",
    "plt.xlabel('X 坐标', fontsize=14)\n",
    "plt.ylabel('Y 坐标', fontsize=14)\n",
    "plt.title('局部优化后的等边三角形阵列', fontsize=16)\n",
    "plt.legend(fontsize=12)\n",
    "plt.grid(True)\n",
    "\n",
    "# 优化图像展示\n",
    "plt.tight_layout()\n",
    "# plt.show()\n",
    "plt.savefig('two2.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d9ec7ba-7a82-4041-b734-1c134d49a8bd",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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